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@article{Demortain2023,

title = {Mistrust of the black box: the public auditing of private models in the chemicals regulatory space},

author = {David Demortain},

url = {https://doi.org/10.1080/09505431.2023.2286278},

doi = {10.1080/09505431.2023.2286278},

year  = {2023},

date = {2023-12-06},

journal = {Science as Culture},

abstract = {Metrics foster trust in governing bodies, but their uncertainty can elicit an opposite sentiment of mistrust. In chemicals governance, most of the conversations concerning computational models revolve around their uncertainty, and the extent to which simulations of safe doses can be transposed in regulatory decisions. To understand the source of this mistrust in models, research in science and technology studies on policy modeling, particularly research that looks at models as an interface between science and policy, must be extended to consider the private production of predictions. Looking at the full set of actors involved in predictive regulatory knowledge – companies, regulatory agencies, modelers working with one or the other – and their concurrent articulations of uncertainty, it appears that regulators audit physiologically based pharmacokinetic models (PBPK, a key class of models used to compute safe chemical doses), because the chemical industry initially introduced them to challenge its methods of risk assessment. Regulators and their modelers established model auditing, to be able to negotiate the predictive claims of companies and their consultants. At the end of the day, neither companies nor regulators appear to dominate the production of predictive knowledge. It is the product of the shifting distribution of expertise in the regulatory space, and of the outcomes of the recurrent trials of credibility that this distribution enables.},

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pubstate = {published},

tppubtype = {article}

}

@article{Boudalia2022,

title = {The exploration and exploitation of shale gas in Algeria: Surveying key developments in the context of climate uncertainty},

author = {Sofiane Boudalia and Sheila A. Okoth and Rabah Zebsa},

url = {https://www.sciencedirect.com/science/article/pii/S2214790X22000806},

doi = {/10.1016/j.exis.2022.101115},

issn = {2214-790X},

year  = {2022},

date = {2022-09-01},

journal = {The Extractive Industries and Society},

volume = {11},

pages = {101115},

abstract = {Algeria ratified the 2015 Paris Agreement on Climate Change which is committed to reduce greenhouse gas emissions through renewable energy promotion, expanding forest areas and improving water resources. However, the exploration and the exploitation of shale gas are authorized in Algeria. Here, we discuss the socioeconomic factors that have led Algeria to authorize shale gas exploitation regardless of the potential effects of hydraulic fracturing on biodiversity loss and human health under climate change uncertainty context. Data reported show the difficulty to understand the multifaceted aspect of shale gas impacts. Indeed, without a comprehensive environmental assessment (air, soil, water and biodiversity) and human health impacts under climate change context, there is no clear evidence regarding the real costs, on the one hand, and the palpable benefits, on the other, of shale gas exploitation. Scientific data actualization and fully recognizing evidence in the literature are recommended when evaluating the potential adverse effects of unconventional gas on human and animal health, and also when creating hydraulic fracturing legislation. The development of alternative ecofriendly tools and methods to fossil energy sources (e.g., solar photovoltaics, wind, and geothermal energy) has become an emergency to help diversify the economy and safeguard natural resources for future generations.},

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pubstate = {published},

tppubtype = {article}

}

@article{Bordignon2021b,

title = {Over‐promotion and caution in abstracts of preprints during the COVID ‐19 crisis},

author = {Frederique Bordignon and Liana Ermakova and Marianne Noël},

url = {https://onlinelibrary.wiley.com/doi/10.1002/leap.1411},

doi = {https://doi.org/10.1002/leap.1411},

year  = {2021},

date = {2021-07-21},

urldate = {2021-07-21},

organization = {Learned Publishing},

abstract = {The abstract is known to be a promotional genre where researchers tend to exaggerate the benefit of their research and use a promotional discourse to catch the reader's attention. The COVID-19 pandemic has prompted intensive research and has changed traditional publishing with the massive adoption of preprints by researchers. Our aim is to investigate whether the crisis and the ensuing scientific and economic competition have changed the lexical content of abstracts. We propose a comparative study of abstracts associated with preprints issued in response to the pandemic relative to abstracts produced during the closest pre-pandemic period. We show that with the increase (on average and in percentage) of positive words (especially effective) and the slight decrease of negative words, there is a strong increase in hedge words (the most frequent of which are the modal verbs can and may). Hedge words counterbalance the excessive use of positive words and thus invite the readers, who go probably beyond the ‘usual’ audience, to be cautious with the obtained results. The abstracts of preprints urgently produced in response to the COVID-19 crisis stand between uncertainty and over-promotion, illustrating the balance that authors have to achieve between promoting their results and appealing for caution.},

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pubstate = {published},

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}

@article{Cardon2020,

title = {Bounded Futures: Growing a Boundary Foreknowledge Infrastructure in Food Security Research},

author = {Vincent Cardon},

doi = {10.1177/0971721819889918},

year  = {2020},

date = {2020-03-03},

urldate = {2020-03-03},

journal = {Science, Technology and Society},

volume = {25},

number = {1},

pages = {38-66},

abstract = {One preferred way of coping with the openness or indeterminacy of future is to elaborate ‘fictional expectations’ that enable action by defining possible outcomes. In this article, I propose to focus on the career of the impact foresight model to analyse how agro-economists combine imaginaries, narratives, data and calculative technologies addressing the long-term future of agriculture. Impact is a partial equilibrium model, which has become increasingly comprehensive. Its modular structure now enables it to interweave scenarios produced by other legitimate institutions, and to run simulations for a number of configurations of climate change and socio-economic evolutions.In this article, foresight models are taken to be material discursive devices. My argument is that their evolutions as technologies and the framing of the future they operate should not be analysed separately. Transforming radical uncertainty into controlled variability – magnitude of change, they explicitly endeavour to ‘bound’ uncertainty. But it is ‘bounded’ in a way that is highly dependent on the knowledge infrastructure upon which the models rely. Quantified modelling also makes it possible for economists to compare rival models and create alignments or negotiate zones of consensus, that is, a certain form of knowledge on the future. In the case under scrutiny, technological choices and data processing work contribute to reinforce a certain point of view – market, production and technology-oriented – on food security. Studying infrastructure and model design therefore allows a better understanding of path dependency and cognitive lock-in effects regarding the way the future is envisaged and narrated.},

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pubstate = {published},

tppubtype = {article}

}

@article{Demortain2019,

title = {Modèles d’effets, effets des modèles. Calcul des doses et pouvoir industriel dans la gouvernance des produits chimiques.},

author = {David Demortain },

url = {https://www.cairn.info/revue-anthropologie-des-connaissances-2019-4-page-1063.htm},

doi = {https://doi.org/10.3917/rac.045.1063},

year  = {2019},

date = {2019-04-01},

urldate = {2019-04-01},

journal = {Revue d'anthropologie des connaissances},

volume = {13},

number = {4},

pages = {1063-1096},

abstract = {The prediction of health risks is underpinned by the ambition to measure the hazards facing human populations, when it is impossible to test these hazards. It is sometimes suspected that model-based predictions of risk are inherently favorable to the interests of regulated industries: by staging the possibility to measure future risks with precision, modeling harms the credibility of the other kinds of evidence that are used by regulatory agencies to establish risks, such as experiments on animals or studies on humans. In effect, the use of models would delay or even prevent agencies from being able to estimate risks, and would eventually halt their decision-making. This article provides a history of the development and use of the Physiologically Based Pharmacokinetic (PBPK) modeling technique to verify whether it has such an effect on the governance of chemicals. It shows that the effects of models on regulatory decision-making are often limited, for one main reason: models, their theoretical construction, and their parameters or outputs, are routinely evaluated by the modelers who work for regulatory agencies. Models do not therefore set the risk, but open a space for interpreting the value of different forms of knowledge about those risks. The political effects of modeling, and the extent to which they strengthen the power of one or the other actor in the governance of chemicals, depends on the position of this very actor in configurations of uncertainty, or the set of networks that control the evaluation of knowledge and of their uncertainties. From this perspective, the power of the industry is far from being absolute. },

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pubstate = {published},

tppubtype = {article}

}

@article{Robinson2018,

title = {Innovation pathways in additive manufacturing: Methods for tracing emerging and branching paths from rapid prototyping to alternative applications},

author = {Douglas K.R. Robinson and Axel Lagnau and Wouter P.C. Boon},

url = {https://doi.org/10.1016/j.techfore.2018.07.012},

doi = {10.1016/j.techfore.2018.07.012},

year  = {2018},

date = {2018-07-26},

urldate = {2018-07-26},

journal = {Technological Forecasting and Social Change},

abstract = {In recent years, the Forecasting Innovation Pathway approach (FIP) has shown to be a promising set of tools to capture potential developments in emerging fields through capturing indications of endogenous futures. However, the FIP approach is reliant on a clear demarcated area to study, a challenge for emerging technology fields where uncertainty and rhetoric abound. This paper presents an addition to the FIP toolbox that helps characterise and demarcate boundaries of emerging fields to allow for deeper analysis through other FIP methods. We illustrate this approach through an exercise for 3D printing technology (also known as Additive Manufacturing). We show that 3D printing can be represented by a dominant design: a tri-partite configuration of printer, material and digital design software. In the past decade we have seen significant branching from applications in rapid-prototyping to medical, fashion, aeronautics and supply chain management with a variety of elements coming together in tri-partite configurations. The paper adds to the current FTA literature an approach building on evolutionary theories of technical change to help with such situations – emerging, evolving and branching ‘innovation pathways’. Moreover, we developed a methodology to construct these innovation paths.},

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}